US20260017306
2026-01-15
Physics
G06F16/338
The invention introduces a system that combines programmatic control with a guided and constrained AI engine to generate personalized video responses for users. Users provide inputs to identify a historical figure and ask a question directed to this figure. The system retrieves relevant information such as the image, voice identifier, and biographical profile of the historical figure. The AI engine analyzes the question, generates a response, and integrates it with audio and visual components to simulate the historical figure delivering the dialogue. This personalized video response is then provided to users on an online learning platform.
This invention pertains to electronics, specifically video response generation systems aimed at enhancing educational platforms. Traditional educational content often lacks interactivity and personalization, which can disengage students. Historical figures typically appear in static content, limiting real-time interaction. This system addresses these limitations by providing dynamic, personalized content that adapts to individual student inquiries, thereby enhancing engagement and learning.
The method involves executing code using computer processors to perform operations based on user input. Users select a historical figure and pose a question. The system retrieves the figure's image, voice identifier, and biographical profile. A language learning model (LLM) analyzes the question, generating a response based on historical context. The response is integrated with audio and visual elements to simulate the historical figure delivering the dialogue. A prompt guides the AI engine to generate a video response, which is then provided to the user on an online learning platform.
The system comprises processors and memory storing code to perform operations when executed. It receives user input to identify a historical figure and a question. It retrieves relevant information and utilizes an LLM to analyze the question. The LLM generates a dialogue response, which is integrated with the retrieved information to produce a video response. This response includes audio and visual components to simulate the historical figure. The AI engine is guided by prompts to ensure accurate and relevant video generation, which is then shared with the user.
This system addresses technical challenges in generating personalized video responses by automating processes that were previously manual and inefficient. It uses AI engines with specific guidance and constraints to achieve desired outcomes. Prompts guide and constrain AI engines to produce reliable outputs, avoiding issues like hallucinations and irrelevant responses. This method changes how AI systems operate, providing a technical solution to generate personalized, interactive educational content.